class_docstr: Represents a reference to a SQL table.
docstr: Parses a SqlTable from string input found in a user-provided model specification.
  
  Raises a ValueError on any non-string input, as all user-provided specifications of table entities
  should be strings conforming to the expectations defined in the from_string method.
docstr_tok: ["Parses","a","SqlTable","from","string","input","found","in","a","user-provided","model","specification",".","Raises","a","ValueError","on","any","non-string","input",",","as","all","user-provided","specifications","of","table","entities","should","be","strings","conforming","to","the","expectations","defined","in","the","from_string","method","."]
code: def _from_yaml_value(
      cls, input: PydanticParseableValueType
  ) -> SqlTable:
      """Parses a SqlTable from string input found in a user-provided model specification.
  
      Raises a ValueError on any non-string input, as all user-provided specifications of table entities
      should be strings conforming to the expectations defined in the from_string method.
      """
      if isinstance(input, str):
          return SqlTable.from_string(input)
      else:
          raise ValueError(
              f"SqlTable inputs from model configs are expected to always be of type string, but got type "
              f"{type(input)} with value: {input}"
          )
  
file_path: metricflow/metricflow/dataflow/sql_table.py
imports: from __future__ import annotations
  from typing import Optional, Tuple, Union
  from dbt_semantic_interfaces.implementations.base import FrozenBaseModel, PydanticCustomInputParser, PydanticParseableValueType
label_desc: Use image node_id 1 for calling the SqlTable obj's underlying member method code with example usage: obj._from_yaml_value(cls, input) and returns: SqlTable